Gal A. Kaminka's Publications

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Leading a Best-Response Teammate in an Ad Hoc Team

Peter Stone, Gal A. Kaminka, and Jeff S. Rosenschein. Leading a Best-Response Teammate in an Ad Hoc Team. In Proceedings of the AAMAS 2009 workshop on Agent-Mediated Electronic Commerce (AMEC), 2009.

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Abstract

Teams of agents may not always be developed in a planned, coordinated fashion. Rather, as deployed agents become more common in e-commerce and other settings, there are increasing opportunities for previously unacquainted agents to cooperate in ad hoc team settings. In such scenarios, it is useful for individual agents to be able to collaborate with a wide variety of possible teammates under the philosophy that not all agents are fully rational. This paper considers an agent that is to interact repeatedly with a teammate that will adapt to this interaction in a particular suboptimal, but natural way. We formalize this setting in game-theoretic terms, provide and analyze a fully-implemented algorithm for finding optimal action sequences, prove some theoretical results pertaining to the lengths of these action sequences, and provide empirical results pertaining to the prevalence of our problem of interest in random interaction settings.

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BibTeX

@InProceedings{amec09,
author = {Peter Stone and Gal A. Kaminka and Jeff S. Rosenschein},
title = {Leading a Best-Response Teammate in an Ad Hoc Team},
booktitle = {Proceedings of the {AAMAS} 2009 workshop on Agent-Mediated Electronic Commerce ({AMEC})},
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OPTpages = {},
year = {2009},
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OPTvolume = {},
OPTnumber = {},
OPTseries = {},
OPTaddress = {},
OPTmonth = {},
OPTorganization = {},
OPTpublisher = {},
OPTnote = {},
OPTannote = {},
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OPTlocalfile = {},
  abstract = {Teams of agents may not always be developed in a planned, coordinated 
fashion.  Rather, as deployed agents become more common in e-commerce 
and other settings, there are increasing opportunities for previously  
unacquainted agents to cooperate in ad hoc team settings.  In such  
scenarios, it is useful for individual agents to be able to 
collaborate with a wide variety of possible teammates under the 
philosophy that not all agents are fully rational.  This paper 
considers an agent that is to interact repeatedly with a teammate that 
will adapt to this interaction in a particular suboptimal, but natural 
way.  We formalize this setting in game-theoretic terms, provide and 
analyze a fully-implemented algorithm for finding optimal action 
sequences, prove some theoretical results pertaining to the lengths of 
these action sequences, and provide empirical results pertaining to 
the prevalence of our problem of interest in random interaction settings. },
  wwwnote = {}, 
}

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